[Docs] Zero-to-Hero notebooks and quick start documentation (#368)

Co-authored-by: Kai Wu <kaiwu@meta.com>
Co-authored-by: Sanyam Bhutani <sanyambhutani@meta.com>
Co-authored-by: Justin Lee <justinai@fb.com>

docs/zero_to_hero_guide/quickstart.md

@@ -0,0 +1,191 @@
+# Llama Stack Quickstart Guide
+
+This guide will walk you through setting up an end-to-end workflow with Llama Stack, enabling you to perform text generation using the `Llama3.2-3B-Instruct` model. Follow these steps to get started quickly.
+
+If you're looking for more specific topics like tool calling or agent setup, we have a [Zero to Hero Guide](#next-steps) that covers everything from Tool Calling to Agents in detail. Feel free to skip to the end to explore the advanced topics you're interested in.
+
+## Table of Contents
+1. [Setup](#Setup)
+2. [Build, Configure, and Run Llama Stack](#build-configure-and-run-llama-stack)
+3. [Testing with `curl`](#testing-with-curl)
+4. [Testing with Python](#testing-with-python)
+5. [Next Steps](#next-steps)
+
+---
+
+
+
+## Setup
+
+### 1. Prerequisite
+
+Ensure you have the following installed on your system:
+
+- **Conda**: A package, dependency, and environment management tool.
+
+
+### 2. Installation
+The `llama` CLI tool helps you manage the Llama Stack toolchain and agent systems. Follow these step to install
+
+First activate and activate your conda environment
+```
+conda create --name my-env
+conda activate my-env
+```
+Then install llama-stack with pip, you could also check out other installation methods [here](https://llama-stack.readthedocs.io/en/latest/cli_reference/index.html).
+
+```bash
+pip install llama-stack
+```
+
+After installation, the `llama` command should be available in your PATH.
+
+### 3. Download Llama Models
+
+Download the necessary Llama model checkpoints using the `llama` CLI:
+
+```bash
+llama download --model-id Llama3.2-3B-Instruct
+```
+
+Follow the CLI prompts to complete the download. You may need to accept a license agreement. Obtain an instant license [here](https://www.llama.com/llama-downloads/).
+
+---
+
+## Build, Configure, and Run Llama Stack
+
+### 1. Build the Llama Stack Distribution
+
+We will default to building the `meta-reference-gpu` distribution due to its optimized configuration tailored for inference tasks that utilize local GPU capabilities effectively. If you have limited GPU resources, prefer using a cloud-based instance or plan to run on a CPU, you can explore other distribution options [here](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html#decide-your-inference-provider).
+
+```bash
+llama stack build --template meta-reference-gpu --image-type conda
+```
+
+
+### 2. Run the Llama Stack Distribution
+> Launching a distribution initializes and configures the necessary APIs and Providers, enabling seamless interaction with the underlying model.
+
+Start the server with the configured stack:
+
+```bash
+cd llama-stack/distributions/meta-reference-gpu
+llama stack run ./run.yaml
+```
+
+The server will start and listen on `http://localhost:5000` by default.
+
+---
+
+## Testing with `curl`
+
+After setting up the server, verify it's working by sending a `POST` request using `curl`:
+
+```bash
+curl http://localhost:5000/inference/chat_completion \
+-H "Content-Type: application/json" \
+-d '{
+    "model": "Llama3.2-3B-Instruct",
+    "messages": [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Write me a 2-sentence poem about the moon"}
+    ],
+    "sampling_params": {"temperature": 0.7, "seed": 42, "max_tokens": 512}
+}'
+```
+
+**Expected Output:**
+```json
+{
+  "completion_message": {
+    "role": "assistant",
+    "content": "The moon glows softly in the midnight sky,\nA beacon of wonder, as it catches the eye.",
+    "stop_reason": "out_of_tokens",
+    "tool_calls": []
+  },
+  "logprobs": null
+}
+```
+
+---
+
+## Testing with Python
+
+You can also interact with the Llama Stack server using a simple Python script. Below is an example:
+
+### 1. Install Required Python Packages
+The `llama-stack-client` library offers a robust and efficient python methods for interacting with the Llama Stack server.
+
+```bash
+pip install llama-stack-client
+```
+
+### 2. Create Python Script (`test_llama_stack.py`)
+```bash
+touch test_llama_stack.py
+```
+
+### 3. Create a Chat Completion Request in Python
+
+```python
+from llama_stack_client import LlamaStackClient
+from llama_stack_client.types import SystemMessage, UserMessage
+
+# Initialize the client
+client = LlamaStackClient(base_url="http://localhost:5000")
+
+# Create a chat completion request
+response = client.inference.chat_completion(
+    messages=[
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Write a two-sentence poem about llama."}
+    ],
+    model="Llama3.2-3B-Instruct",
+)
+
+# Print the response
+print(response.completion_message.content)
+```
+
+### 4. Run the Python Script
+
+```bash
+python test_llama_stack.py
+```
+
+**Expected Output:**
+```
+The moon glows softly in the midnight sky,
+A beacon of wonder, as it catches the eye.
+```
+
+With these steps, you should have a functional Llama Stack setup capable of generating text using the specified model. For more detailed information and advanced configurations, refer to some of our documentation below.
+
+---
+
+## Next Steps
+
+**Explore Other Guides**: Dive deeper into specific topics by following these guides:
+- [Understanding Distribution](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html#decide-your-inference-provider)
+- [Inference 101](00_Inference101.ipynb)
+- [Local and Cloud Model Toggling 101](00_Local_Cloud_Inference101.ipynb)
+- [Prompt Engineering](01_Prompt_Engineering101.ipynb)
+- [Chat with Image - LlamaStack Vision API](02_Image_Chat101.ipynb)
+- [Tool Calling: How to and Details](03_Tool_Calling101.ipynb)
+- [Memory API: Show Simple In-Memory Retrieval](04_Memory101.ipynb)
+- [Using Safety API in Conversation](05_Safety101.ipynb)
+- [Agents API: Explain Components](06_Agents101.ipynb)
+
+
+**Explore Client SDKs**: Utilize our client SDKs for various languages to integrate Llama Stack into your applications:
+  - [Python SDK](https://github.com/meta-llama/llama-stack-client-python)
+  - [Node SDK](https://github.com/meta-llama/llama-stack-client-node)
+  - [Swift SDK](https://github.com/meta-llama/llama-stack-client-swift)
+  - [Kotlin SDK](https://github.com/meta-llama/llama-stack-client-kotlin)
+
+**Advanced Configuration**: Learn how to customize your Llama Stack distribution by referring to the [Building a Llama Stack Distribution](./building_distro.md) guide.
+
+**Explore Example Apps**: Check out [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/examples) for example applications built using Llama Stack.
+
+
+---